Observation of specific ion effects in humus aggregation process

Specific ion effects play a vital role in a variety of colloidal and interfacial processes.However,few studies have reported the specific ion effects in the humus aggregation process,which strongly influence the transport and fate of environmental pollutants.In this study,soil humus colloids were prepared and characterized,and the specific ion effects on humus aggregation in electrolyte solutions were investigated at a variety of concentrations and pH values using dynamic light scattering methods.Activation energy(ΔE),which is known to reflect the dynamics and stability of a colloidal system,was used to quantitatively characterize the specific ion effects.The results showed that given ΔE value of 2.48×10^(3) J mol^(-1) at pH 3.0,the electrolyte concentrations were 91.6,58.2,3.8,and 0.8 mmol L^(-1) for Na^(+),K^(+),Mg^(2+),and Ca_(2+),respectively,thus indicating significant specific ion effects in the humus aggregation process.Most importantly,decreasing the electrolyte concentrations increased the differences in the ΔE value between two cation species with the same valence(i.e.,ΔE_(Na)-ΔE_(K) and ΔE_(Mg)-ΔE_(Ca)),while increasing the pH increased the magnitude of ΔE_(Mg)-ΔE_(Ca).However,the classic Derjaguin,Landau,Verwey,and Overbeek(DLVO)theory and the double layer theory,as well as the currently widely used ionic hydration and dispersion effects,failed to predict the experimentally observed increase in the specific ion effects with decreasing electrolyte concentrations in a quantitative sense.These results have implications for the necessity of involving specific ion effects for a better understanding of humus aggregation and interactions in aqueous and soil systems.

Distributed Control of Thermostatically Controlled Loads in Distribution Network with High Penetration of Solar PV

High penetration of solar energy can result in voltage rise in midday,while growth in residential air conditioning is the main contributor of overloading and voltage drop issues during peak demand time.This paper provides a hierarchical control scheme to coordinate multiple groups of aggregated thermostatically controlled loads to regulate network loading and voltage in a distribution network.Considering the limited number of messages that can be exchanged in a realistic communication environment,an event-triggered distributed control strategy is proposed in this paper.Through intermittent on and off toggling of air conditioners,the required active power adjustment is shared among participating aggregators to solve the issue.A case study is conducted and simulation results are presented to demonstrate the performance of the proposed control scheme.

Coordinated expansion co-planning of integrated gas and power systems

As a significant clean energy source, natural gas plays an important role in modern energy context. The growing utilization of natural gas brings uncertainties into the power system, which requires an integrated way to plan natural gas and power systems. In this paper, the co-planning process is formulated as a mixed integer nonlinear programming problem to address emerging challenges,such as system reliability evaluation, market time line mismatch, market uncertainties, demand response effect,etc. An innovative expansion co-planning(ECP) framework is established in this paper to find the best augmentation plan which comes with the minimum cost.Specifically, to cope with uncertainties in market share,decision analysis is introduced. Meanwhile, the energy conversion efficiency between gas and electricity in the coupled load center is considered in the ECP constraints.Comprehensive case studies are applied to validate the performance of proposed approach.

Optimal air-conditioning load control in distribution network with intermittent renewables

The coordinated operation of controllable loads,such as air-conditioning load, and distributed generation sources in a smart grid environment has drawn significant attention in recent years. To improve the wind power utilization level in the distribution network and minimize the total system operation costs, this paper proposes a MILP(mixed integer linear programming) based approach to schedule the interruptible air-conditioning loads. In order to mitigate the uncertainties of the stochastic variables including wind power generation, ambient temperature change, and electricity retail price, the rolling horizon optimization(RHO) strategy is employed to continuously update the real-time information and proceed the control window. Moreover, to ensure the thermal comfort of customers, a novel two-parameter thermal model is introduced to calculate the indoor temperature variation more precisely. Simulations on a five node radial distribution network validate the efficiency of the proposed method.